Definition
A keyword cluster is a group of keywords and questions that share the same search intent and should therefore be answered by one page. 'Shopify SEO', 'SEO for Shopify store', 'improve Shopify visibility' and 'Shopify SEO tips' together form one cluster: whoever types these terms wants the same thing, and Google shows largely the same results for them.
Clustering replaces the old approach of one keyword per page. Since updates such as Hummingbird, RankBrain and BERT, search engines understand that different phrasings express the same need. Creating a separate page for every variant produces thin pages that cannibalise each other. Bundling all variants on one strong page ranks for the whole cluster at once.
There are two ways to cluster. Semantic clustering looks at the meaning of the words and groups what belongs together in substance. SERP clustering looks at the search results: if two terms share at least three or four of the same URLs in the top ten, Google treats them as the same intent. SERP clustering is more reliable, because it measures what the search engine actually does rather than what a tool assumes.
A cluster has a head term (the term with the most volume or the clearest intent) and a set of supporting terms. The head term sets the title and H1; the supporting terms get a place in subheadings, paragraphs and the FAQ. Clusters in turn connect in a topical map: a pillar page on 'Shopify SEO' with cluster pages on Shopify collections, product pages, speed and apps.
Clusters are also the basis for measurement. You do not track a single keyword but the visibility of the whole group, in Google and in AI answers. Traze clusters automatically based on SERP overlap and AI questions, writes one page per cluster and reports visibility per cluster, so you can see which topic is growing and which needs attention.